
jev-use
Claude Code / Codex / pi plugin that hands agent steps needing no text output to Jev (TypeSafe's judgment model) — measured p50 ~230 ms and ~$0.02 per 1,000…
Install with your AI
Paste into Claude Code, Cursor, or any agent — it reads the repo and wires the tool into your project.
Install and set up jev-use (claude-plugin project) into my current project. Found on https://claudeers.com/jev-use Repo: https://github.com/shitianfang/jev-use Homepage/docs: https://www.npmjs.com/package/jev-use Detected install method: claude-plugin → /plugin install jev-use@shitianfang/jev-use Category: mcp-servers. Platforms: cli, api. Read the repo's README for exact setup and env vars, then install it and wire it into my project. Claudeers Health Verdict: active; community-verified: false. Confirm the source before running anything.
/plugin marketplace add shitianfang/jev-use /plugin install jev-use@shitianfang/jev-use
git clone https://github.com/shitianfang/jev-use
// compatibility
| Platforms | cli, api |
|---|---|
| Operating systems | — |
| AI compatibility | claude |
| License | MIT |
| Pricing | open-source |
| Language | JavaScript |
jev-use
English | 简体中文
The best way for Claude Code, Codex, and pi to work with Jev: hand the tasks that need no text output to Jev — faster steps, fewer tokens, tasks done sooner and better.
It makes the LLM and Jev true collaborators: when content needs to be written, the LLM takes over; when a step just needs a fast decision, Jev executes it.
Demos — real runs, 1× speed
Directions task: Jev clicks, the LLM types — 10 decisions (p50 274 ms) · 4 writes; Jev rejects a wrong route, the LLM rewrites![]() | Context compaction — 200 messages judged in 7 calls, one LLM paragraph replaces the dropped pile; recall 3/3![]() |
Pong: ball speed = decision latency — 86 Jev decisions in 20 s vs 6 (haiku) and 3 (gemini) called the usual way; enum-constrain both and the gap is 3×![]() | Gate every shell command — dangerous ones denied in ~230 ms with a reason, zero LLM tokens![]() |
Every demo is a rerunnable script in bench/examples/; all numbers, methodology, variance and caveats: bench/RESULTS.md · third-party measurements: docs/evidence.md.
Install
npx -y jev-use install # wires Claude Code, Codex, and pi — whichever it finds
Set one key in the environment your agent runs in (JEV_BACKEND=mock for
a keyless dry run):
| Provider | Env var |
|---|---|
| TypeSafe direct | TYPESAFE_API_KEY |
| OpenRouter | OPENROUTER_API_KEY |
| Vercel AI Gateway | AI_GATEWAY_API_KEY |
npx -y jev-use doctor checks the wiring. Judged state goes to the
provider you configure; JEV_BACKEND=mock stays local. Plugin form with
the routing skill and the PreToolUse gate:
harness/claude-code ·
harness/codex.
Use as a library
npm i jev-use — zero runtime dependencies on the judgment path:
import { Jev, check, pick, rate } from "jev-use";
const jev = new Jev();
const { answers } = await jev.judge(state, {
next: pick("Next action?", { merge: "all green", rerun: "looks flaky", hold: "needs attention" }),
risk: rate("How risky?", ["routine", "worth a look", "incident"]),
passed: check("Did the run fully succeed?"),
});
// answers.next → { answer: "merge", confidence: 0.93, confidenceFrom: "reported", escalate: false }
Anything Jev can't or shouldn't decide comes back with escalate: true
and a typed reason. Tools, verdict shape, escalation contract, CLI:
docs/reference.md.
Small enough to read
| File | Job |
|---|---|
| src/protocol.ts | Questions (check/pick/rate), verdicts, escalation reasons |
| src/dispatch.ts | Pre-call routing: what never reaches Jev |
| src/judge.ts | screen → backend → hand back what is unsure; gate |
| src/jev.ts | The Jev client over that engine |
| src/backends/ | TypeSafe, OpenRouter, Vercel, mock adapters |
| src/server.ts | The two MCP tools |
| src/cli.ts | install, serve, hook gate, doctor |
| skills/jev-use/SKILL.md | The routing rules the agent follows |
Development
$ npm run typecheck && npm test # unit tests incl. per-provider wire fixtures
$ npm run smoke # real MCP client ↔ built CLI over stdio
$ node bench/run.mjs # micro-benchmarks, your key and region
Substantially written with Claude Code (AI-assisted).
MIT © shitianfang
// faq
What is jev-use?
Claude Code / Codex / pi plugin that hands agent steps needing no text output to Jev (TypeSafe's judgment model) — measured p50 ~230 ms and ~$0.02 per 1,000 judgments, with typed escalation back to the LLM. It is open-source on GitHub.
Is jev-use free to use?
jev-use is open-source under the MIT license, so it is free to use.
What category does jev-use belong to?
jev-use is listed under mcp-servers in the Claudeers registry of Claude-compatible tools.
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